.ipynb .pdf

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Compare data from the Disdrometer and Rain Gauge

import xarray as xr
import hvplot.xarray
import hvplot.pandas
import pandas as pd
import holoviews as hv
from distributed import Client, LocalCluster
hv.extension('bokeh')

Spin up a Dask Cluster

cluster = LocalCluster()
client = Client(cluster)
client

distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-7gggry14', purging
distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-gu2trvj7', purging
distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-fosyqxv1', purging
distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-s50t2e4t', purging

Client

Client-17a27cdc-afb3-11ec-9549-acde48001122

Connection method: Cluster object	Cluster type: distributed.LocalCluster
Dashboard: http://127.0.0.1:8787/status

Cluster Info

LocalCluster

94902f8f

Dashboard: http://127.0.0.1:8787/status	Workers: 4
Total threads: 12	Total memory: 16.00 GiB
Status: running	Using processes: True

Scheduler Info

Scheduler

Scheduler-b24d500b-7d4e-42b2-be55-917686657001

Comm: tcp://127.0.0.1:65491	Workers: 4
Dashboard: http://127.0.0.1:8787/status	Total threads: 12
Started: Just now	Total memory: 16.00 GiB

Workers

Worker: 0

Comm: tcp://127.0.0.1:65506	Total threads: 3
Dashboard: http://127.0.0.1:65509/status	Memory: 4.00 GiB
Nanny: tcp://127.0.0.1:65497
Local directory: /Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-ktdval7y

Worker: 1

Comm: tcp://127.0.0.1:65510	Total threads: 3
Dashboard: http://127.0.0.1:65512/status	Memory: 4.00 GiB
Nanny: tcp://127.0.0.1:65496
Local directory: /Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-n63y4mr7

Worker: 2

Comm: tcp://127.0.0.1:65502	Total threads: 3
Dashboard: http://127.0.0.1:65503/status	Memory: 4.00 GiB
Nanny: tcp://127.0.0.1:65494
Local directory: /Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-kxjux7zt

Worker: 3

Comm: tcp://127.0.0.1:65505	Total threads: 3
Dashboard: http://127.0.0.1:65507/status	Memory: 4.00 GiB
Nanny: tcp://127.0.0.1:65495
Local directory: /Users/mgrover/git_repos/SAILS-radar-analysis/notebooks/precipitation-exploration/dask-worker-space/worker-mwjl50pz

Read in the data

Here, we use data from:

• a disdrometer (datastream: gucldM1.b1)

• a rain gauge (datastream: gucwbpluvio2M1.a1)

We use all the data available, you can query from this website: https://adc.arm.gov/discovery/#/

disdrometer_ds = xr.open_mfdataset('../../data/disdrometer/*')
gauge_ds = xr.open_mfdataset('../../data/rain-gauge/*')

Visualize the Data

We use hvplot here to plot an interactive view of our data, utilizing rasterize to dynamically view our large datasets

from bokeh.models import DatetimeTickFormatter

def apply_formatter(plot, element):
    plot.handles['xaxis'].formatter = DatetimeTickFormatter(hours='%m/%d/%Y \n %H:%M',
                                                            minutes='%m/%d/%Y \n %H:%M',
                                                            hourmin='%m/%d/%Y \n %H:%M',
                                                            days='%m/%d/%Y \n %H:%M',
                                                            months='%m/%d/%Y \n %H:%M')

snow_rate_plot = disdrometer_ds.snow_depth_intensity.hvplot.line(ylim=(0, 350), rasterize=True).opts(hooks=[apply_formatter])
bucket_accumulation = gauge_ds.intensity_rtnrt.hvplot.line(ylim=(0, 350), rasterize=True).opts(hooks=[apply_formatter])

View our Final Visualization

We can combine these into a single column of plots, matching the views/colorbars

(snow_rate_plot + bucket_accumulation).cols(1)

previous

Exploring a ZDR Offset Value